technology


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Computers don’t exist in a vacuum. They serve to solve problems, and the type of problems they can solve are influenced by their hardware. Graphics processors are specialized for rendering images; artificial intelligence processors for AI; and quantum computers designed for…what?

While the power of quantum computing is impressive, it does not mean that existing software simply runs a billion times faster. Rather, quantum computers have certain types of problems which they are good at solving, and those which they aren’t. Below are some of the primary applications we should expect to see as this next generation of computers becomes commercially available.

 

Artificial Intelligence

A primary application for quantum computing is artificial intelligence (AI). AI is based on the principle of learning from experience, becoming more accurate as feedback is given, until the computer program appears to exhibit “intelligence.”

This feedback is based on calculating the probabilities for many possible choices, and so AI is an ideal candidate for quantum computation. It promises to disrupt every industry, from automotives to medicine, and it’s been said AI will be to the twenty-first century what electricity was to the twentieth.

For example, Lockheed Martin plans to use its D-Wave quantum computer to test autopilot software that is currently too complex for classical computers, and Google is using a quantum computer to design software that can distinguish cars from landmarks. We have already reached the point where AI is creating more AI, and so its importance will rapidly escalate.

Molecular Modeling

Another example is precision modeling of molecular interactions, finding the optimum configurations for chemical reactions. Such “quantum chemistry” is so complex that only the simplest molecules can be analyzed by today’s digital computers.

Chemical reactions are quantum in nature as they form highly entangled quantum superposition states. But fully-developed quantum computers would not have any difficulty evaluating even the most complex processes.

Google has already made forays in this field by simulating the energy of hydrogen molecules. The implication of this is more efficient products, from solar cells to pharmaceutical drugs, and especially fertilizer production; since fertilizer accounts for 2 percent of global energy usage, the consequences for energy and the environment would be profound.

Cryptography

Most online security currently depends on the difficulty of factoring large numbers into primes. While this can presently be accomplished by using digital computers to search through every possible factor, the immense time required makes “cracking the code” expensive and impractical.

Quantum computers can perform such factoring exponentially more efficiently than digital computers, meaning such security methods will soon become obsolete. New cryptography methods are being developed, though it may take time: in August 2015 the NSA began introducing a list of quantum-resistant cryptography methods that would resist quantum computers, and in April 2016 the National Institute of Standards and Technology began a public evaluation process lasting four to six years.

There are also promising quantum encryption methods being developed using the one-way nature of quantum entanglement. City-wide networks have already been demonstrated in several countries, and Chinese scientists recently announced they successfully sent entangled photons from an orbiting “quantum” satellite to three separate base stations back on Earth.

Financial Modeling

Modern markets are some of the most complicated systems in existence. While we have developed increasingly scientific and mathematical tools to address this, it still suffers from one major difference between other scientific fields: there’s no controlled setting in which to run experiments.

To solve this, investors and analysts have turned to quantum computing. One immediate advantage is that the randomness inherent to quantum computers is congruent to the stochastic nature of financial markets. Investors often wish to evaluate the distribution of outcomes under an extremely large number of scenarios generated at random.

Another advantage quantum offers is that financial operations such as arbitrage may require many path-dependent steps, the number of possibilities quickly outpacing the capacity of a digital computer.

Weather Forecasting

NOAA Chief Economist Rodney F. Weiher claims (PowerPoint file) that nearly 30 percent of the US GDP ($6 trillion) is directly or indirectly affected by weather, impacting food production, transportation, and retail trade, among others. The ability to better predict the weather would have enormous benefit to many fields, not to mention more time to take cover from disasters.

While this has long been a goal of scientists, the equations governing such processes contain many, many variables, making classical simulation lengthy. As quantum researcher Seth Lloyd pointed out, “Using a classical computer to perform such analysis might take longer than it takes the actual weather to evolve!” This motivated Lloyd and colleagues at MIT to show that the equations governing the weather possess a hidden wave nature which are amenable to solution by a quantum computer.

Director of engineering at Google Hartmut Neven also noted that quantum computers could help build better climate models that could give us more insight into how humans are influencing the environment. These models are what we build our estimates of future warming on, and help us determine what steps need to be taken now to prevent disasters.

The United Kingdom’s national weather service Met Office has already begun investing in such innovation to meet the power and scalability demands they’ll be facing in the 2020-plus timeframe, and released a report on its own requirements for exascale computing.

Particle Physics

Coming full circle, a final application of this exciting new physics might be… studying exciting new physics. Models of particle physics are often extraordinarily complex, confounding pen-and-paper solutions and requiring vast amounts of computing time for numerical simulation. This makes them ideal for quantum computation, and researchers have already been taking advantage of this.

Researchers at the University of Innsbruck and the Institute for Quantum Optics and Quantum Information (IQOQI) recently used a programmable quantum system to perform such a simulation. Published in Nature, the team used a simple version of quantum computer in which ions performed logical operations, the basic steps in any computer calculation. This simulation showed excellent agreement compared to actual experiments of the physics described.

“These two approaches complement one another perfectly,” says theoretical physicist Peter Zoller. “We cannot replace the experiments that are done with particle colliders. However, by developing quantum simulators, we may be able to understand these experiments better one day.”

Investors are now scrambling to insert themselves into the quantum computing ecosystem, and it’s not just the computer industry: banks, aerospace companies, and cybersecurity firms are among those taking advantage of the computational revolution.

While quantum computing is already impacting the fields listed above, the list is by no means exhaustive, and that’s the most exciting part. As with all new technology, presently unimaginable applications will be developed as the hardware continues to evolve and create new opportunities.

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This will form the foundation:

(Phys.org)—Researchers have built a new type of “neuron transistor”—a transistor that behaves like a neuron in a living brain. These devices could form the building blocks of neuromorphic hardware that may offer unprecedented computational capabilities, such as learning and adaptation.

The researchers, S. G. Hu and coauthors at the University of Electronic Science and Technology of China and Nanyang Technological University in Singapore, have published a paper on the neuron transistor in a recent issue of Nanotechnology.

In order for a transistor to behave like a biological neuron, it must be capable of implementing neuron-like functions—in particular, weighted summation and threshold functions. These refer to a biological neuron’s ability to receive weighted input signals from many other neurons, and then to sum the input values and compare them to a threshold value to determine whether or not to fire. The human brain has tens of billions of neurons, and they are constantly performing weighted summation and threshold functions many times per second that together control all of our thoughts and actions.

In the new study, the researchers constructed a neuron transistor that acts like a single neuron, capable of weighted summation and threshold functions. Instead of being made of silicon like conventional , the neuron transistor is made of a two-dimensional flake of molybdenum disulfide (MoS2), which belongs to a new class of semiconductor called .

To demonstrate the neuron transistor’s neuron-like behavior, the researchers showed that it can be controlled by either one gate or two gates simultaneously. In the latter case, the neuron transistor implements a summation . To demonstrate, the researchers showed that the neuron transistor can perform a counting task analogous to moving the beads in a two-bead abacus, along with other logic functions.

One of the advantages of the neuron transistor is its operating speed. Although other neuron transistors have already been built, they typically operate at frequencies of less than or equal to 0.05 Hz, which is much lower than the average firing rate of biological  of about 5 Hz. The new neuron transistor works in a wide frequency range of 0.01 to 15 Hz, which the researchers expect will offer advantages for developing neuromorphic hardware.

In the future, the researchers hope to add more control gates to the neuron transistor, creating a more realistic model of a biological neuron with its many inputs. In addition, the researchers hope to integrate neuron transistors with memristors (which are considered to be the most suitable device for implementing synapses) to construct neuromorphic systems that can work in a similar way to the brain.

 

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A NEW commodity spawns a lucrative, fast-growing industry, prompting antitrust regulators to step in to restrain those who control its flow. A century ago, the resource in question was oil. Now similar concerns are being raised by the giants that deal in data, the oil of the digital era. These titans—Alphabet (Google’s parent company), Amazon, Apple, Facebook and Microsoft—look unstoppable. They are the five most valuable listed firms in the world. Their profits are surging: they collectively racked up over $25bn in net profit in the first quarter of 2017. Amazon captures half of all dollars spent online in America. Google and Facebook accounted for almost all the revenue growth in digital advertising in America last year.

Such dominance has prompted calls for the tech giants to be broken up, as Standard Oil was in the early 20th century. This newspaper has argued against such drastic action in the past. Size alone is not a crime. The giants’ success has benefited consumers. Few want to live without Google’s search engine, Amazon’s one-day delivery or Facebook’s newsfeed. Nor do these firms raise the alarm when standard antitrust tests are applied. Far from gouging consumers, many of their services are free (users pay, in effect, by handing over yet more data). Take account of offline rivals, and their market shares look less worrying. And the emergence of upstarts like Snapchat suggests that new entrants can still make waves.

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But there is cause for concern. Internet companies’ control of data gives them enormous power. Old ways of thinking about competition, devised in the era of oil, look outdated in what has come to be called the “data economy” (see Briefing). A new approach is needed.

Quantity has a quality all its own

What has changed? Smartphones and the internet have made data abundant, ubiquitous and far more valuable. Whether you are going for a run, watching TV or even just sitting in traffic, virtually every activity creates a digital trace—more raw material for the data distilleries. As devices from watches to cars connect to the internet, the volume is increasing: some estimate that a self-driving car will generate 100 gigabytes per second. Meanwhile, artificial-intelligence (AI) techniques such as machine learning extract more value from data. Algorithms can predict when a customer is ready to buy, a jet-engine needs servicing or a person is at risk of a disease. Industrial giants such as GE and Siemens now sell themselves as data firms.

This abundance of data changes the nature of competition. Technology giants have always benefited from network effects: the more users Facebook signs up, the more attractive signing up becomes for others. With data there are extra network effects. By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on. The more data Tesla gathers from its self-driving cars, the better it can make them at driving themselves—part of the reason the firm, which sold only 25,000 cars in the first quarter, is now worth more than GM, which sold 2.3m. Vast pools of data can thus act as protective moats.

Access to data also protects companies from rivals in another way. The case for being sanguine about competition in the tech industry rests on the potential for incumbents to be blindsided by a startup in a garage or an unexpected technological shift. But both are less likely in the data age. The giants’ surveillance systems span the entire economy: Google can see what people search for, Facebook what they share, Amazon what they buy. They own app stores and operating systems, and rent out computing power to startups. They have a “God’s eye view” of activities in their own markets and beyond. They can see when a new product or service gains traction, allowing them to copy it or simply buy the upstart before it becomes too great a threat. Many think Facebook’s $22bn purchase in 2014 of WhatsApp, a messaging app with fewer than 60 employees, falls into this category of “shoot-out acquisitions” that eliminate potential rivals. By providing barriers to entry and early-warning systems, data can stifle competition.

Who ya gonna call, trustbusters?

The nature of data makes the antitrust remedies of the past less useful. Breaking up a firm like Google into five Googlets would not stop network effects from reasserting themselves: in time, one of them would become dominant again. A radical rethink is required—and as the outlines of a new approach start to become apparent, two ideas stand out.

The first is that antitrust authorities need to move from the industrial era into the 21st century. When considering a merger, for example, they have traditionally used size to determine when to intervene. They now need to take into account the extent of firms’ data assets when assessing the impact of deals. The purchase price could also be a signal that an incumbent is buying a nascent threat. On these measures, Facebook’s willingness to pay so much for WhatsApp, which had no revenue to speak of, would have raised red flags. Trustbusters must also become more data-savvy in their analysis of market dynamics, for example by using simulations to hunt for algorithms colluding over prices or to determine how best to promote competition (see Free exchange).

The second principle is to loosen the grip that providers of online services have over data and give more control to those who supply them. More transparency would help: companies could be forced to reveal to consumers what information they hold and how much money they make from it. Governments could encourage the emergence of new services by opening up more of their own data vaults or managing crucial parts of the data economy as public infrastructure, as India does with its digital-identity system, Aadhaar. They could also mandate the sharing of certain kinds of data, with users’ consent—an approach Europe is taking in financial services by requiring banks to make customers’ data accessible to third parties.

Rebooting antitrust for the information age will not be easy. It will entail new risks: more data sharing, for instance, could threaten privacy. But if governments don’t want a data economy dominated by a few giants, they will need to act soon.

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How many of you can prove without a shadow of doubt that during the last election your vote was counted? By proof I don’t mean the sticker you received that reads, “I Voted.” I mean a tangible immutable record that proves not only that you stood in line at the polling station but that your vote was counted and was credited to your candidate of choice. Unfortunately, with our current system, the truth is you can’t.

What if I told you there was an existing technology that would allow you to vote anonymously, track your vote, and verify it was counted all without the need for someone else to process it? This technology is called a blockchain – best known for its role as Bitcoin’s underlying technology. Bitcoin is widely known as an alternative currency, but when we look beyond the currency we find a technology that will dramatically change our lives.

As Americans we often think of voter fraud as something that happens elsewhere. We see YouTube videos of foreign ballot boxes being stuffed with counterfeit votes and trust that can’t happen here. However, with allegations of a “rigged” election, the possibility of voter fraud has cast doubt on the electoral process. This suspicion could be completely removed with a blockchain based voting system.

Blockchain technology guarantees three essential elements of a fair and free election: anonymity, immutability, and traceability. It does all this automatically without the need for a trusted third party, thus removing any doubt about the validity of an election. Blockchain technology uses cryptography to anonymously record and transmit your vote while ensuring that the process is tamper-proof. Additionally, you can watch the entire process unfold, from the time you place the vote to the time the vote is counted. Even more remarkable is that you will walk away with a permanent record of your vote that can never be changed.

The Bitcoin blockchain has been in existence since 2009 and has never been hacked. Every single transaction that has taken place with bitcoin is permanently and immutably stored in the blockchain. The high profile “hacks” that we read about are not hacks of the blockchain, they are hacks of applications that run on top of the secure Bitcoin blockchain. This is an important distinction-even when these third party applications are hacked not a single transaction on the Bitcoin blockchain has been changed. Immutability is not just essential when recording financial transactions, it is also imperative when counting votes.

Some of the world’s largest financial institutions have seen the promise of blockchain technology, with likes of the Barlcays, Goldman Sachs, NYSE and NASDAQ – to name a few- all beginning to use it for financial transactions. And now it is being used to count votes as well.

The Abu Dhabi Securities Exchange (ADX) announced that they are deploying a blockchain voting service. This new service will not only allow investors to participate in the voting at an Annual General Meeting, it will also allow them to observe the vote. This initiative parallels efforts by Dubai to create a blockchain enabled smart city.

E-voting using a blockchain is not some futuristic dream – it is already happening. Blockchain based government elections have already occurred in Denmark and are gaining traction in Norway and Spain. And now thanks to a company called Follow My Vote, U.S. citizens can use blockchain technology to vote in a parallel 2016 Presidential election.

The U.S. electoral process is one of the most sacred rights we enjoy as citizens. A fair and free election is fundamental to our democracy and we deserve unwavering faith in this process. Blockchain technology is one way we can ensure that the rights we enjoy are safeguarded and that every eligible vote is counted and credited correctly. No more hanging chads, no more voting “early and often” and no more doubt about our election.

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This video shows the Tesla driving itself.

https://www.tesla.com/videos/full-self-driving-hardware-all-tesla-cars?curator=thereformedbroker&utm_source=thereformedbroker

Is driving purely functional, A to B, or is it also entertainment? I ride my bikes not to get to A to B, although that can be true, but for the sheer joy of riding a bike as fast as I can to my ability.

I’m assuming that you [currently] can choose which mode to put the car in. However, how long will it be before government mandates only the car can drive. No issues about speeding, drink driving, etc. Of course then all you need is a box on wheels.

Will you pay a premium for your box. Hell no.

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Ray Kurzweil, the author, inventor, computer scientist, futurist and Google employee, was the featured keynote speaker Thursday afternoon at Postback, the annual conference presented by Seattle mobile marketing company Tune. His topic was the future of mobile technology. In Kurzweil’s world, however, that doesn’t just mean the future of smartphones — it means the future of humanity.

Continue reading for a few highlights from his talk.

On the effect of the modern information era: People think the world’s getting worse, and we see that on the left and the right, and we see that in other countries. People think the world is getting worse. … That’s the perception. What’s actually happening is our information about what’s wrong in the world is getting better. A century ago, there would be a battle that wiped out the next village, you’d never even hear about it. Now there’s an incident halfway around the globe and we not only hear about it, we experience it.

Which is why the perception that someone like Trump sells, could be false and misleading. But more importantly, what actions we take based upon that information. If I respond differently, then my perception has directly changed my actions, which has unforseen ramifications when multiplied by millions.

Brexit could be an example of exactly this.

On the potential of human genomics: It’s not just collecting what is basically the object code of life that is expanding exponentially. Our ability to understand it, to reverse-engineer it, to simulate it, and most importantly to reprogram this outdated software is also expanding exponentially. Genes are software programs. It’s not a metaphor. They are sequences of data. But they evolved many years ago, many tens of thousands of years ago, when conditions were different.

Clearly our genome is not exactly the same. It to has evolved. This may have been through random mutations, in which certain recipients thrived in a changing environment.

How technology will change humanity’s geographic needs: We’re only crowded because we’ve crowded ourselves into cities. Try taking a train trip across the United States, or Europe or Asia or anywhere in the world. Ninety-nine percent of the land is not used. Now, we don’t want to use it because you don’t want to be out in the boondocks if you don’t have people to work and play with. That’s already changing now that we have some level of virtual communication. We can have workgroups that are spread out. … But ultimately, we’ll have full-immersion virtual reality from within the nervous system, augmented reality.

One of my favorite novels is Asimov’s “Foundation” series. The planet Trantor….entirely covered by a city. Is that what we want?

On connecting the brain directly to the cloud: We don’t yet have brain extenders directly from our brain. We do have brain extenders indirectly. I mean this (holds up his smartphone) is a brain extender. … Ultimately we’ll put them directly in our brains. But not just to do search and language translation and other types of things we do now with mobile apps, but to actually extend the very scope of our brain.

The mobile phone as a brain extender. Possibly true for 1% of all users. Most use facebook or whatever other time wasting application, and essentially gossip. A monumental waste of time. Far from being a brain extender, for most, it is the ultimate dumbing down machine. Text language encourages bad spelling, poor grammar etc. So you can keep your brain extenders.

As far as directly connecting your brain to the cloud….that sounds like ‘The Matrix”, which is of course the subject of philosophical musings about the brain in a vat. The potential for mind control would seem to be a possibility here. Not for me thanks.

Why machines won’t displace humans: We’re going to merge with them, we’re going to make ourselves smarter. We’re already doing that. These mobile devices make us smarter. We’re routinely doing things we couldn’t possibly do without these brain extenders.

To date, I would argue that the vast majority are significantly more stupid because of them.

As to robots and AI, imagine a man, Spock, who’s choice making is driven 100% by logic, rather than by 50% logic and 50% emotion. How long does the emotional decision maker last? Most emotional decisions get us in trouble. The market is an excellent example. Politics is another, ie. Trump.

 

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At its core, the blockchain is a technology that permanently records transactions in a way that cannot be later erased but can only be sequentially updated, in essence keeping a never-ending historical trail. This seemingly simple functional description has gargantuan implications. It is making us rethink the old ways of creating transactions, storing data, and moving assets, and that’s only the beginning.

The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping everything along its way by the force of its progression. Plainly, it is the second significant overlay on top of the Internet, just as the Web was that first layer back in 1990. That new layer is mostly about trust, so we could call it the trust layer.

Blockchains are enormous catalysts for change that affect governance, ways of life, traditional corporate models, society and global institutions. Blockchain infiltration will be met with resistance, because it is an extreme change.

Blockchains defy old ideas that have been locked in our minds for decades, if not centuries. Blockchains will challenge governance and centrally controlled ways of enforcing transactions. For example, why pay an escrow to clear a title insurance if the blockchain can automatically check it in an irrefutable way?

Blockchains loosen up trust, which has been in the hands of central institutions (e.g., banks, policy makers, clearinghouses, governments, large corporations), and allows it to evade these old control points. For example, what if counterparty validation can be done on the blockchain, instead of by a clearinghouse?

An analogy would be when, in the 16th century, medieval guilds helped to maintain monopolies on certain crafts against outsiders, by controlling the printing of knowledge that would explain how to copy their work. They accomplished that type of censorship by being in cahoots with the Catholic Church and governments in most European countries that regulated and controlled printing by requiring licenses. That type of central control and monopoly didn’t last too long, and soon enough, knowledge was free to travel after an explosion in printing. To think of printing knowledge as an illegal activity would be unfathomable today. We could think of the traditional holders of central trust as today’s guilds, and we could question why they should continue holding that trust, if technology (the blockchain) performed that function as well or even better.

Blockchains liberate the trust function from outside existing boundaries in the same way as medieval institutions were forced to cede control of printing.

It is deceptive to view the blockchain primarily as a distributed ledger, because it represents only one of its many dimensions. It’s like describing the Internet as a network only, or as just a publishing platform. These are necessary but not sufficient conditions or properties; blockchains are also greater than the sum of their parts.

Blockchain proponents believe that trust should be free, and not in the hands of central forces that tax it, or control it in one form or another (e.g., fees, access rights, or permissions). They believe that trust can be and should be part of peer-to-peer relationships, facilitated by technology that can enforce it. Trust can be coded up, and it can be computed to be true or false by way of mathematically-backed certainty, that is enforced by powerful encryption to cement it. In essence, trust is replaced by cryptographic proofs, and trust is maintained by a network of trusted computers (honest nodes) that ensure its security, as contrasted with single entities who create overhead or unnecessary bureaucracy around it.

If blockchains are a new way to implement trusted transactions without trusted intermediaries, soon we’ll end up with intermediary-less trust. Policy makers who regulated “trusted” institutions like banks will face a dilemma. How can you regulate something that is evaporating? They will need to update their old regulations.

Intermediary-controlled trust came with some friction, but now, with the blockchain, we can have frictionless trust. So, when trust is “free” (even if it still needs to be earned), what happens next? Naturally, trust will follow the path of least resistance, and will become gradually decentralized towards the edges of the network.

Blockchains also enable assets and value to be exchanged, providing a new, speedy rail for moving value of all kinds without unnecessary intermediaries.

As back-end infrastructure, blockchains are metaphorically the ultimate, non-stop computers. Once launched, they never go down, because of the incredible amount of resiliency they offer.

There is no single point of failure unlike how bank systems have gone down, cloud-based services have gone down, but bona fide blockchains keep computing.

The Internet was about replacing some intermediaries. Now the blockchain is about replacing other intermediaries once again. But it’s also about creating new ones. And so was the Web. Current intermediaries will need to figure out how their roles will be affected, while others are angling to take a piece of the new pie in the race to “decentralize everything.”

The world is preoccupied with dissecting, analyzing and prognosticating on the blockchain’s future; technologists, entrepreneurs, and enterprises are wondering if it is to be considered vitamin or poison.

Today, we’re saying blockchain does this or that, but tomorrow blockchains will be rather invisible; we will talk more about what they enable. Just like the Internet or the Web, and just like data-bases, the blockchain brings with it a new language.

From the mid-1950s forward, as IT evolved, we became accustomed to a new language: mainframes, databases, networks, servers, software, operating systems, and programming languages. Since the early 1990s, the Internet ushered in another lexicon: browsing, website, Java, blogging, TCP/IP, SMTP, HTTP, URLs, and HTML. Today, the blockchain brings with it yet another new repertoire: consensus algorithms, smart contracts, distributed ledgers, oracles, digital wallets, and transaction blocks.

Block by block, we will accumulate our own chains of knowledge, and we will learn and understand the blockchain, what it changes, and the implications of such change.

Today, we Google for everything, mostly information or products.

Tomorrow, we will perform the equivalent of “googling” to verify records, identities, authenticity, rights, work done, titles, contracts, and other valuable asset-related processes. There will be digital ownership certificates for everything. Just like we cannot double spend digital money anymore (thanks to Satoshi Nakamoto’s invention), we will not be able to double copy or forge official certificates once they are certified on a blockchain. That was a missing piece of the information revolution, which the blockchain fixes.

I still remember the initial excitement around being able to track a shipped package on the Web when FedEx introduced this capability for the first time in 1994. Today, we take that type of service for granted, but this particular feature was a watershed use case that demonstrated what we could do on the early Web. The underlying message was that a previously enclosed private service could become openly accessible by anyone with Internet access. A whole host of services followed: online banking, filing taxes, buying products, trading stocks, checking on orders, and many others. Just as we access services that search public databases, we will search a new class of services that will check blockchains to confirm the veracity of information. Information access will not be enough. We will also want to ask for truth access, and we will ask if modifications were made to particular records, expecting the utmost transparency from those who hold them. The blockchain promises to serve up and expose transparency in its rawest forms.

The old question “Is it in the database?” will be replaced by “Is it on the blockchain?”

Is the blockchain more complicated than the Web? Most definitely.

The blockchain is part of the history of the Internet. It is at the same level as the World Wide Web in terms of importance, and arguably might give us back the Internet, in the way it was supposed to be: more decentralized, more open, more secure, more private, more equitable, and more accessible. Ironically, many blockchain applications also have a shot at replacing legacy Web applications, at the same time as they will replace legacy businesses that cannot loosen their grips on heavy-handed centrally enforced trust functions.

No matter how it unfolds, the blockchain’s history will continue to be written for a very long time, just as the history of the Web continued to be written well after its initial invention. But here’s what will make the blockchain’s future even more interesting: you are part of it.


Reprinted from The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology by William Mougayar (foreword from Vitalik Buterin) with permission from John Wiley & Sons, Inc. Copyright (C) William Mougayar, 2016.

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